title: Composite likelihood-based meta-analysis of breast cancer association studies.
abstract: For detecting low risk disease variants in genome-wide association panels, meta-analysis is a powerful strategy to increase power. We apply a composite likelihood-based method, which models association with disease in regions defined on a linkage disequilibrium map and combines the evidence across multiple genome-wide samples. This fixed region approach has the advantage that, as only one statistical test is made per region, there is no increased multiple testing penalty in higher marker density panels. Imputation of missing genotypes is also advantageous to increase coverage. Meta-analysis of three breast cancer data sets combines evidence from samples that show heterogeneity in phenotype and, particularly, in marker coverage. The FGFR2 gene has the highest rank, consistent with previous analysis of one of these samples and supported by the small number of early-onset breast cancer cases included. The 8q24 breast cancer region also ranks highly and is supported by evidence from both early-onset and post-menopausal breast cancer samples. The PIK3AP1 gene region is highlighted in this analysis as a strong candidate for further study.
authors.affiliation: Genetic Epidemiology and Bioinformatics Research Group, Human Genetics Research Division, University of Southampton, School of Medicine, Southampton General Hospital, Hampshire, UK.
authors.forename: Ioannis
authors.initials: I
authors.lastname: Politopoulos
authors.forename: Jane
authors.initials: J
authors.lastname: Gibson
authors.forename: William
authors.initials: W
authors.lastname: Tapper
authors.forename: Sarah
authors.initials: S
authors.lastname: Ennis
authors.forename: Diana
authors.initials: D
authors.lastname: Eccles
authors.forename: Andrew
authors.initials: A
authors.lastname: Collins
mesh_terms: D048868:Adaptor Proteins, Signal Transducing / Q000235:genetics; D001943:Breast Neoplasms / Q000235:genetics*; D002874:Chromosome Mapping; D002898:Chromosomes, Human, Pair 8 / Q000235:genetics; D005260:Female; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D015810:Linkage Disequilibrium; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D051497:Receptor, Fibroblast Growth Factor, Type 2 / Q000235:genetics
chemical_list: D048868:Adaptor Proteins, Signal Transducing; C487977:PIK3AP1 protein, human; D051497:Receptor, Fibroblast Growth Factor, Type 2